Scaling arguments can be provided to estimate \(k_{c}^{+}(\tau _{b},N_{b})\) 
and \(k_{c}^{-}(\tau _{b},N_{b})\) , as discussed in details in [1]}.
However, the actual values depend on the underlying probability distribution
of the process, and in complex applications they have to be estimated
case by case by empirical analysis. A simple way to proceed is to
compute the relative contribution of the largest value to the sample
mean
\(r(k,\tau _{b},N_{b})=\frac{e^{kA_{\tau _{b}}^{max}}}{\sum _{j=1}^{N_{b}}e^{kA_{\tau _{b}}^{j}}}.\) 
